The mainstay of the telephone company local network is the local subscriber loop. The local subscriber loop is now being used to provide broadband digital telecommunication services such as DSL service. Such broadband DSL services include integrated services digital subscriber network (“ISDN”), high-rate digital subscriber line (“HDSL”), asymmetrical digital subscriber lines (“ADSL”) and very high rate digital subscriber lines (“VDSL”) technology. DSL services allow residential and business customers to send and/or receive digital data at higher rates of speed than were previously possible using analog modem technology.
DSL technologies are engineered to operate over a class of subscriber loops, such as nonloaded loops (18 kft) or Carrier Serving Area (CSA) loops (9 to 12 kft). Digital Subscriber Line (DSL) technology exploits the existing, ubiquitous, copper telephone loop plant to provide megabit per second (Mbps) high-speed Internet access and other services.
The great majority of residential customers and many business customers are served by such metallic (copper) twisted pair cables connected from a local switch in the central office (“CO”) to the subscriber's land-line telephones. For each subscriber, telephone and DSL signals travel on a single twisted pair from a central office (CO) to the subscriber. Many, sometimes thousands, of twisted pairs are wrapped together in a single cable. The twisting of the pairs keeps the average amount of electromagnetic coupling between the balanced circuits on each pair to a low level, resulting in low crosstalk coupling between different circuits at voice frequencies. Twisted-pair cabling was designed and built to carry voice services, requiring only a very low probability of intelligible crosstalk at voice frequencies, generally up to a few kHz.
Crosstalk generally increases, however, with increasing frequency, and because DSL frequencies extend into the MegaHertz (“MHz”) range, crosstalk becomes the major limitation to high-speed DSL. Because a number of individual twisted pairs are wrapped together in a binder, and a number of binders are in each telephone cable (there are typically 12, 13, 25, 50 or 100 pairs in a binder) the crosstalk between pairs in the same binder is much higher than it is between pairs in different binders. Telephone cabling can be thought of as a multi-input, multi-output interference channel with crosstalk in-between from 12 to 100 channels, although there are typically a smaller number of high-power crosstalkers in each pair.
DSL technology is still fairly new. The general approach to date has been to treat each signal on each twisted pair entirely separately, and to assume that crosstalk is simply additive Gaussian noise of which nothing is known. With this approach, subscribers can enjoy relatively high-speed service, far faster than voice-band modems, up to multiple Megabits per second (“Mbps”). This is the current static approach to DSL spectrum management.
As time progresses it is expected that there will be many more DSL users each demanding higher speed service. This will result in more crosstalk and higher-bandwidth services that are more vulnerable to crosstalk. Without accurate systems and methods for identifying crosstalk, canceling such crosstalk and thereby carefully managing the available frequency spectrum in local loop plants there may be no way to avoid problems that will ultimately result in customer disappointment, delay and higher costs.
The American National Standards Institute (ANSI) Working Group T1E1.4, being responsible for DSL standards on ISDN Basic Access, HDSL and ADSL, initiated a project in 1998 to develop relevant standards for spectrum management. ANSI Standard T1.417-2001, Spectrum Management for Loop Transmission Systems, was approved and issued in January 2001. This ANSI standard applies relatively rigid rules uniformly across the entire loop plant. There have been a number of proposals for new DSL systems, for example the class of symmetric DSL (“SDSL”). Unfortunately, this creativity complicates the problem of spectrum management, as is apparent from Table 1, which shows the nine currently agreed classes of DSL systems.
TABLE 1Spectrum Management ClassesDeploymentSpectrumGuideline, maxManagementloop length EWLIncluded DSL(SM) Class26 gauge kftTechnologiesClass 1all nonleaded loopsISDNSDSL ≦ 300 kbps2-line & 4-line DAMLCIass 211.5 kftSDSL ≦ 512 kbpsClass 3  9 kftHDSL and 784 kbpsSDSLClass 410.5 kftHDSL2 (single-pairHDSL)Class 5all nonloaded loopsADSL, CAP/QAMRADSL, G.lite(partial-overlapped)Class 6Not definedVDSLClass 7 6.5 kftSDSL ≦ 1568 kbpsClass 8 7.5 kftSDSL ≦ 1168 kbpsClass 913.5 kftOverlapped, echo-canceled ADSL
FIG. 8 shows currently adopted power spectral density (“PSD”) templates for each of these spectrum management classes except Class 6 with line 110 representing Class 1 and line 180 representing Class 9 with the others represented respectively in between. To comply with the ANSI standard, the PSD of the signal transmitted by a piece of equipment must fall under the template at all frequencies. This will generally be verified during manufacture, but if problems arise in the field the local operator will need to resolve incompatibilities and complaints, possibly including identification of systems that are transmitting in violation of the standard.
Current rules for DSL spectrum management assume static worst case crosstalk types and crosstalk couplings. These rules do not take into account the individual types of crosstalk sources or crosstalk couplings related to a particular pair in a cable, which may be considerably different than the near worst-case couplings that are assumed in the ANSI standard. Dynamic spectrum management would take into account the individual types of crosstalk sources and crosstalk couplings of each particular cable, and could greatly increase the number of customers that can be provided DSL service and their bit rates. Thus, a system that can characterize crosstalk on a loop-by-loop basis has the potential to yield a better crosstalk characterization of the plant. Furthermore, the use of such crosstalk data in a loop spectrum management database, in turn has the potential to be mined, correlated and exploited to provide more optimal performances for individual subscriber loops.
It would be desirable to have a technique that could characterize the crosstalk environment on a loop-by-loop basis, in a mechanized and highly accurate manner without the need for special equipment or intervention at the subscriber's location.
Further it would be desirable to use the automated system for the identification of crosstalk for the spectrum management of DSL systems.
Therefore, it is desirable to have a means for identifying crosstalk between local loops that will enable a system operator to identify actual or potential crosstalk disturbers depending on the configuration of the DSL services being provided to a plurality of customers.